Video-based speed detection and other such traffic monitoring applications have become increasingly prevalent in modern society. In order for such monitoring to provide accurate data, the tracking cameras must be calibrated.
In speed detection applications, it is critical that the cameras used to collect video are calibrated. Proper improper calibration can create significant error in the ultimate speed determination. For example, if a tracking camera has a 5% magnification along the direction of travel due to incorrect calibration or change of focus, any speed detection from the camera will have a corresponding 5% bias.
Prior art methods and systems exist for calibrating cameras. However, these methods and systems use static calibration targets for camera calibration. This may include, for example, placing a static checkerboard in the camera's field of view. However, the use of these techniques requires that either the camera be relocated somewhere that does not disturb traffic, or the static target be placed such that they do not disturb traffic. Placing the targets inherently requires traffic diversion. This may include creating a roadwork zone where traffic is stopped so that the targets can be placed.
In addition, the use of static targets can distract motorists as they pass the targets, and closing roads for camera calibration is costly for society. Therefore, improved methods and systems are necessary for cost-effective and accurate camera calibration.